IP Library Granted Patent US 10,354,514
Granted Patent B1
US 10,354,514 · App. 16/189,866 · Granted Jul 16, 2019

Detecting and handling material left in vehicles by transportation requestors

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Quick Facts
Patent No.
US 10,354,514
App. No.
16/189,866
Granted
Jul 16, 2019
Kind
B1
Abstract

The present disclosure includes embodiments of systems, methods, and computer readable media that enable a dynamic transportation system to detect when material has been left in a vehicle by a requestor. In some embodiments, the system detects the completion of the transportation request, analyzes data from a plurality of vehicle sensors, from a computing device associated with the vehicle, and from a computing device associated with the requestor, and then determines, based on the data analysis, that material has been left in the vehicle. The system then performs an action for handling the material based on one or more attributes of the material.

Claims (68)

1. A method comprising:

analyzing data from one or more sensors associated with a vehicle, a computing device associated with the vehicle, and a requestor computing device associated with a transportation requestor, wherein analyzing the data comprises comparing motion data from the requestor computing device to motion data from the computing device associated with the vehicle to identify any consistencies between the motion data from the requestor computing device and the motion data from the computing device associated with the vehicle;

based on analyzing the data from the one or more sensors, determining whether material has been left in the vehicle; and

based on determining that material has been left in the vehicle, determining an action that corresponds to the material that has been left in the vehicle.

2. The method as recited in claim 1 , further comprising:

detecting that the transportation requestor exits the vehicle; and

analyzing the data from the one or more sensors in response to detecting that the transportation requestor exits the vehicle.

3. The method as recited in claim 1 , wherein analyzing the data further comprises:

comparing a geographic location of the requestor computer device to a geographic location of the computing device associated with the vehicle to determine whether the requestor computing device is within a threshold distance of the computing device associated with the vehicle after the transportation requestor exits the vehicle.

4. The method as recited in claim 1 , wherein analyzing the data further comprises:

determining a signal strength between the requestor computing device and the computing device associated with the vehicle; and

determining, based on the signal strength, whether the requestor computing device is within a threshold distance of the computing device associated with the vehicle after the transportation requestor exits the vehicle.

5. The method as recited in claim 1 , wherein the one or more sensors comprise one or more of a camera, a motion sensor, an audio sensor, a pressure sensor, a moisture sensor, or an olfactory sensor.

6. The method as recited in claim 1 , further comprising:

determining one or more attributes of the material left in the vehicle based on the data from the one or more sensors; and

identifying the material based on the one or more attributes of the material.

7. The method as recited in claim 1 , wherein the action comprises at least one of:

cancelling or preventing a subsequent transportation request associated with the vehicle;

initiating a communication with the computing device associated with the vehicle;

initiating a communication with the transportation requestor;

dispatching the vehicle to a predetermined location or to a location of the transportation requestor; or

causing the vehicle to emit a sound.

8. The method as recited in claim 1 , further comprising:

determining that the action was ineffective; and

in response to determining that the action was ineffective, determining a second action corresponding to the material left in the vehicle.

9. The method as recited in claim 1 , further comprising:

utilizing a machine learning model to calculate, based on the data from the one or more sensors, a confidence score indicating a likelihood that the material has been left in the vehicle; and

identifying the material that has been left in the vehicle based on the confidence score.

10. A system comprising:

at least one processor; and

at least one non-transitory computer readable storage medium storing instructions thereon that, when executed by the at least one processor, cause the system to:

analyze data from one or more sensors associated with a vehicle, a computing device associated with the vehicle, and a requestor computing device associated with a transportation requestor, wherein analyzing the data comprises comparing motion data from the requestor computing device to motion data from the computing device associated with the vehicle to identify any consistencies between the motion data from the requestor computing device and the motion data from the computing device associated with the vehicle;

based on analyzing the data from the one or more sensors, determine whether material has been left in the vehicle; and

based on determining that material has been left in the vehicle, determine an action that corresponds to the material that has been left in the vehicle.

11. The system as recited in claim 10 , further comprising instructions that, when executed by the at least one processor, cause the system to:

detect that the transportation requestor exits the vehicle; and

analyze the data from the one or more sensors in response to detecting that the transportation requestor exits the vehicle.

12. The system as recited in claim 10 , wherein analyzing the data further comprises:

comparing a geographic location of the requestor computer device to a geographic location of the computing device associated with the vehicle to determine whether the requestor computing device is within a threshold distance of the computing device associated with the vehicle after the transportation requestor exits the vehicle.

13. The system as recited in claim 10 , further comprising instructions that, when executed by the at least one processor, cause the system to:

determine a signal strength between the requestor computing device and the computing device associated with the vehicle; and

determine, based on the signal strength, whether the requestor computing device is within a threshold distance of the computing device associated with the vehicle after the transportation requestor exits the vehicle.

14. A non-transitory computer readable storage medium comprising instructions that, when executed by at least one processor, cause a computer system to:

analyze data from one or more sensors associated with a vehicle, a computing device associated with the vehicle, and a requestor computing device associated with a transportation requestor, wherein analyzing the data comprises comparing motion data from the requestor computing device to motion data from the computing device associated with the vehicle to identify any consistencies between the motion data from the requestor computing device and the motion data from the computing device associated with the vehicle;

based on analyzing the data from the one or more sensors, determine whether material has been left in the vehicle; and

based on determining that material has been left in the vehicle, determine an action that corresponds to the material that has been left in the vehicle.

15. The non-transitory computer readable storage medium of claim 14 , wherein the one or more sensors comprise one or more of a camera, a motion sensor, an audio sensor, a pressure sensor, a moisture sensor, or an olfactory sensor.

16. The non-transitory computer readable storage medium of claim 14 , further comprising instructions that, when executed by the at least one processor, cause the computer system to:

determine one or more attributes of the material left in the vehicle based on the data from the one or more sensors; and

identify the material based on the one or more attributes of the material.

17. The non-transitory computer readable storage medium of claim 14 , wherein the action comprises at least one of:

cancelling or preventing a subsequent transportation request associated with the vehicle;

initiating a communication with the computing device associated with the vehicle;

initiating a communication with the transportation requestor;

dispatching the vehicle to a predetermined location or to a location of the transportation requestor; or

causing the vehicle to emit a sound.

18. The non-transitory computer readable storage medium of claim 14 , further comprising instructions that, when executed by the at least one processor, cause the computer system to:

determine that the action was ineffective; and

in response to determining that the action was ineffective, determine a second action corresponding to the material left in the vehicle.

19. The system as recited in claim 10 , wherein the action comprises at least one of:

cancelling or preventing a subsequent transportation request associated with the vehicle;

initiating a communication with the computing device associated with the vehicle;

initiating a communication with the transportation requestor;

dispatching the vehicle to a predetermined location or to a location of the transportation requestor; or

causing the vehicle to emit a sound.

20. The non-transitory computer readable storage medium of claim 14 , further comprising instructions that, when executed by the at least one processor, cause the computer system to:

determine a signal strength between the requestor computing device and the computing device associated with the vehicle; and

determine, based on the signal strength, whether the requestor computing device is within a threshold distance of the computing device associated with the vehicle after the transportation requestor exits the vehicle.

Assignments (2)
SECURITY INTEREST Recorded Nov 3, 2022
From: LYFT, INC.
To: JPMORGAN CHASE BANK, N.A., AS ADMINISTRATIVE AGENT
Reel/Frame 061880/0237 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 13, 2018
From: HWANG, THADDEUS INSUK; GARMS, JESSE MICHAEL; VINCENT, LUC
To: LYFT, INC.
Reel/Frame 047490/0990 →